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作者：Rodriguez-Caballero, C. Vladimir; Ruiz, Esther
作者单位：Instituto Tecnologico Autonomo de Mexico; Universidad Carlos III de Madrid
摘要：We propose a Multilevel Dynamic Factor Model (ML-DFM) to capture the common global and region-specific stochastic trends in monthly centre and log-range temperatures observed at 68 locations across the Iberian Peninsula from January 1930 to December 2020. The specification of common trends is based on the analysis of temperatures at each location using unobserved component models, which decompose temperatures into trend, seasonal, and transitory components. First, we show that the centre and l...
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作者：He, Yuheng; Zou, Changliang; Zhao, Yi
作者单位：Nankai University; Indiana University System; Indiana University Bloomington
摘要：In the high-dimensional landscape, addressing the challenges of covariance regression with high-dimensional predictors has posed difficulties for conventional methodologies. This paper addresses these hurdles by presenting a novel approach for high-dimensional inference with covariance matrix outcomes. The proposed methodology is demonstrated through its application in identifying patterns of brain co-activation observed in functional magnetic resonance imaging (fMRI) experiments and in reveal...
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作者：Stevenson, Ben c.; Smit, Elizabeth; Setyawan, Edy
作者单位：University of Auckland
摘要：An understanding of the body size of individuals and the relationships between different dimensions is critical for monitoring the status and the health of a wildlife population. Morphometric data have traditionally been collected by physically handling and measuring individual animals, but recent technological advancements allow researchers to deploy sophisticated but affordable instruments, like drones and camera traps, to take photos of individual animals from which morphometric measurement...
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作者：Zhou, Wenbin; Zhu, Shixiang
作者单位：Carnegie Mellon University
摘要：The rapid growth of distributed energy resources (DERs) presents both opportunities and operational challenges for electric grid management. Accurately predicting DER adoption is critical for proactive infrastructure planning, but the inherent uncertainty and spatial disparity of DER growth complicate traditional forecasting approaches. Moreover, the hierarchical structure of distribution grids demands that predictions satisfy statistical guarantees at both the circuit and substation levels, a...
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作者：Du, Mingyue; Lou, Yichen; Sun, Jianguo
作者单位：Jilin University; Nanyang Technological University; Southern University of Science & Technology
摘要：This paper discusses regression analysis of interval-censored failure time data, which often occur in many areas and for which a great deal of literature has been established. In addition, many authors have investigated the analysis of failure time data with either change points or informative censoring, and as interval censoring, both can also separately occur in many situations such as clinical medicine and precision medicine. However, it does not seem to exist an established approach that c...
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作者：Antonelli, Joseph; Rubinstein, Max; Agniel, Denis; Smart, Rosanna; Stuart, Elizabeth A.; Cefalu, Matthew; Schell, Terry; Eagan, Joshua; Stone, Elizabeth; Griswold, Max; Griffin, Beth Ann
作者单位：State University System of Florida; University of Florida; RAND Corporation; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
摘要：Motivated by the study of state opioid policies, we propose a novel approach using autoregressive models for causal effect estimation in panel data settings. We estimate the impact of key opioid-related policies, specifically must-access prescription drug monitoring programs (PDMPs), naloxone access laws (NALs), and medical marijuana laws, on opioid prescribing. Existing methods, such as difference-in-differences and synthetic controls, are difficult to apply in dynamic policy environments wit...
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作者：Reiter, Lars N.; Hoffmann, Adam G.; Heide-Jorgensen, Mads Peter; Garde, Eva; Samson, Adeline; Ditlevsen, Susanne
作者单位：University of Copenhagen; Greenland Institute of Natural Resources; Communaute Universite Grenoble Alpes; Universite Grenoble Alpes (UGA)
摘要：Signals with varying periodicity frequently appear in real-world phenomena, necessitating the development of efficient modelling techniques to map the measured nonlinear timeline to linear time. Here we propose a regression model that allows for a representation of periodic and dynamic patterns observed in time series data. The model incorporates a hidden strictly positive stochastic process that represents the instantaneous frequency, allowing the model to adapt and accurately capture varying...
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作者：Jeong, Cheoljoon; Byon, Eunshin
作者单位：Clemson University; University of Michigan System; University of Michigan
摘要：Parameter calibration seeks to estimate unobservable parameters in a computer model by aligning field observations with computer model outputs. In the building energy sector, a physics-based computer model is developed to analyze building energy use, given various weather conditions and operational scenarios. To obtain accurate simulations, it is necessary to calibrate model parameters required for preconfiguration. Among various techniques, Bayesian optimization stands out for its potential b...
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作者：Wang, You-gan; Foo, Chuan hui
作者单位：Guangdong University of Finance & Economics; Universiti Pendidikan Sultan Idris
摘要：The discontinuous moulting process in crustaceans poses fundamental challenges for growth modelling and can lead to biologically implausible estimates of asymptotic size under traditional continuous-growth frameworks such as the von Bertalanffy curve. We develop a stochastic growth model that jointly characterises moult increment (MI) and intermoult period (IP) through a unified convolution-based likelihood. Individual growth is represented within a L & eacute;vy-inspired jump framework that e...
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作者：Cheung, Ying Kuen; Kuhn, Louise
作者单位：Columbia University; Columbia University
摘要：In a diagnostic test using multiplex assay, each individual biomarker is often expected to have monotonic association with the disease outcome, and, therefore, the underlying disease classification rule is partially ordered with respect to the biomarkers. Nonparametric estimation of the classification rule can be accomplished by projecting an unconstrained Bayes estimator onto the partial ordering subspace. However, computing the projection is challenging as it involves performing maximization...
